Параллелизм, конкурентность и AsyncIO в Python — на примерах

Эта статья рассматривает, как ускорить операции, ограниченные процессором (CPU-bound) и вводом-выводом (IO-bound), с помощью многопроцессорности, многопоточности и AsyncIO.

# tasks.py

import os
from multiprocessing import current_process
from threading import current_thread

import requests


def make_request(num):
    # io-bound

    pid = os.getpid()
    thread_name = current_thread().name
    process_name = current_process().name
    print(f"{pid} - {process_name} - {thread_name}")

    requests.get("https://httpbin.org/ip")


async def make_request_async(num, client):
    # io-bound

    pid = os.getpid()
    thread_name = current_thread().name
    process_name = current_process().name
    print(f"{pid} - {process_name} - {thread_name}")

    await client.get("https://httpbin.org/ip")


def get_prime_numbers(num):
    # cpu-bound

    pid = os.getpid()
    thread_name = current_thread().name
    process_name = current_process().name
    print(f"{pid} - {process_name} - {thread_name}")

    numbers = []

    prime = [True for i in range(num + 1)]
    p = 2

    while p * p <= num:
        if prime[p]:
            for i in range(p * 2, num + 1, p):
                prime[i] = False
        p += 1

    prime[0] = False
    prime[1] = False

    for p in range(num + 1):
        if prime[p]:
            numbers.append(p)

    return numbers

https://testdriven.io/blog/python-concurrency-parallelism/

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